• 한국경영과학회지
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• 제26권1호
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• pp.15-32
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• 2001

It is well known that the web design is composed of several factors which are interacting with each other. However, the current approach to web design had been focused on modifying specific factors without considering its impact on other factors. In this sense, we propose more holistic approach to the web design by using fuzzy cognitive map. For this purpose, we form an illustrative fuzzy cognitive map for the web design which is based on the literature, and analyzed and impact of change in a specific factor on other factors. Especially, to improve the output analyzability, we suggested an advanced version of fuzzy cognitive map called stratified fuzzy cognitive map. After simulating the fuzzy cognitive map for web design, we could conclude that our approach is robust and effective compared to the traditional web design approach.

• 제어로봇시스템학회논문지
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• 제7권6호
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• pp.509-517
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• 2001

To deal with non-linearities and time-varying characteristics of hydraulic systems, in this paper, the neuro-fuzzy controller has been introduced. This controller does not require and accurate mathematical model for the nonlinear factor. In order to solve general fuzzy inference problems, the input membership function and fuzzy reasoning rules are used for determining the controller parameters. These parameters are determined by using the learning algorithm. The control performance of the neuro-fuzzy controller is evaluated through a series of experiments for the various types of inputs while applying disturbances to the hydraulic system. The performance of this controller was compared with those of PID and PD controllers. From these results, We observe be said that the position tracking performance of neuro-fuzzy is better those of PID and PD controllers.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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• pp.153-156
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• 1999

In this paper, we design a GA-fuzzy precompensated PID controller for the load frequency control of two-area interconnected power system. Here, a fuzzy precompensated PID controller is designed as a fuzzy logic-based precompensation approach for PID controller. This scheme is easily implemented simply by adding a fuzzy precompensator to an existing PID controller. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor membership function and control rules.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.228-228
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• 2000

To deal with non-linearities and time-varying characteristics of hydraulic systems, in this paper, the neuro-fuzzy controller has been introduced. This controller does not require an accurate mathematical model for the nonlinear factor. In order to solve general fuzzy inference problems, the input membership function and fuzzy reasoning rules are used for determining the controller Parameters. These parameters are determined by using the learning algorithm. The control performance of the neuro-fuzzy controller is obtained through a series of experiments for the various types of input while applying disturbances to the cylinder. .and performance of this controller was compared with that of PID, PD controller. As a experimental result, it can be proven that the position tracking performance of the neuro-fuzzy is better than that of PID and PD controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 A
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• pp.137-139
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• 2001

In this paper, we design a GA-fuzzy precompensator for enhancement of power system stability. Here, a fuzzy precompensator is designed as a fuzzy logic-based precompensation approach for Power System Stabilizer(PSS). This scheme is easily implemented simply by adding a fuzzy precompensator to an existing PSS. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, name1y, scaling factor, membership function and control rules. Simulation results show that the proposed control technique is superior to a conventional PSS in dynamic responses over the wide range of operating conditions and is convinced robustness and reliableness in view of structure.

• 제어로봇시스템학회논문지
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• 제12권6호
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• pp.561-567
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• 2006

This paper deals with a fuzzy controller using IA(Immune Algorithm) for Trajectory Tracking of 2-DOF WMR(Wheeled Mobile Robot). The global inputs to the WMR are reference position and reference velocity, which are time variables. The global output of WMR is a current position. The tracking controller makes position error to be converged 0. In order to reduce position error, a compensation velocities on the track of trajectory is necessary. Therefore, a FIAC(Fuzzy-IA controller) is proposed to give velocity compensation in this system. Input variables of fuzzy part are position errors in every sampling time. The output values of fuzzy part are compensation velocities. IA are implemented to adjust the scaling factor of fuzzy part. The computer simulation is performed to get the result of trajectory tracking and to prove efficiency of proposed controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2669-2671
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• 2001

In this paper, we propose design a Multi-Fuzzy Inference model structure. In order to determine structure of the proposed Multi-Fuzzy Inference model, HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy are identified by genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy model and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

• Journal of Advanced Marine Engineering and Technology
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• 제34권1호
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• pp.109-115
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• 2010

본 논문은 퍼지 제어를 통한 이동용 로봇에 대한 추적 제어에 대해서 다루고 있다. 이동용 로봇은 Mamdani 형식의 퍼지 제어기로 제어 된다. 퍼지 제어기에 있어서 이동용 로봇과 목표 사이의 각도와 각도의 변화율이 입력으로 사용되고, 출력으로 조향각이 추론되어 제어입력이 된다. 퍼지 규칙은 전문가의 경험적 지식을 참조하여 7개를 사용하였다. 또한 퍼지 제어기 설계에 있어서 하나의 관심 분야인 환산계수(scaling factor) 조정 방법에 대해 제안한다. 본 논문에서는 이를 위해 파라미터 최적화 분야에서 잘 알려진 실수코딩 유전알고리즘을 적용하였다. 시뮬레이션을 통해 다양한 초기 조향각이 주어진 경우, 목표치에 대한 추적 안정성을 보여 퍼지 제어기의 유효성이 확인된다.

• 감성과학
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• 제16권3호
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• pp.333-340
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• 2013

생활양식이나 형태 변화에 따른 전통적인 주거건축들의 전통성, 공공성과 사유권의 균형, 계승 발전, 보존에 부가되는 공동체의 활성화와 효용성 등 환경 개선이라는 과제에 직면하고 있으며, 이들 역사 경관 권역의 경관훼손 가능성이 점증하고 있는 상황에서, 지역적 경관의 고유한 특성과 다양성을 가질 수 있도록 전통적 주거건축의 입면디자인 속성에 대한 이해가 선행되어야 한다. 본 연구는 "전통적 주거건축의 입면디자인 평가"에 영향을 미친 속성을 파악하기 위해, 입면디자인 평가척도 (지붕, 창호, 기둥, 벽면, 마루, 주초석, 기단)를 기준으로 쌍대비교를 실시하여 도출된 Synthetic Evaluation Value를 Fuzzy 방법을 통해 Fuzzy Integral (Choquet Integral) value를 추정하여, 가치속성을 규명하였다. 속성 간 가중치 산정결과에 ${\lambda}$-value를 이용하여 Sensitivity Analysis를 실시하여 유효함을 검증하였다. 전통적 주거건축의 입면디자인 평가에 영향을 미친 가치속성을 추정하는데 있어 유의미한 방법론이며, 복합 가치속성을 도출하였다는데 의의를 갖는다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.415-418
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• 2003

Fuzzy modelling has the approximation property far the given input-output relationship. Especially, Takagi-Sugeno fuzzy models are widely used because they show very good performance in the nonlinear function approximation problem. But generally there is not the systematic method incorporating the human expert's knowledge or experience in fuzzy rules and it is not easy to End the membership function of fuzzy rule to minimize the output error as well. The ANFIS (Adaptive Network-based Fuzzy Inference Systems) is one of the neural network based fuzzy modelling methods that can be used with various type of fuzzy rules. But in this model, it is the problem to End the optimum number of fuzzy rules in fuzzy model. In this paper, a new fuzzy modelling method based on the ANFIS and pruning techniques with the measure named impact factor is proposed and the performance of proposed method is evaluated with several simulation results.